Show HN: Oodle.ai – $10 per million agent traces

Hi HN, we're Kiran and Vijay!

Over the past two years, we have built a columnar storage engine for observability: logs, metrics, and traces. Today, it's exciting for us to show what we've built on top of that foundation: LLM Agent Observability.

Given how non-deterministic agents are, storing all traces without sampling was critical for us. But these traces tend to be in the MBs, sometimes GBs - we needed to store them inexpensively. We also needed the queries and analyses to be fast. To meet both these goals, we store them in S3 in our own parquet-like file format, and query them using AWS Lambda.

Since we process each span of every trace, instead of running LLM-based evals on each, we first analyze them using deterministic techniques. We detect tool failures, retries, loops, abnormal token usage, latency regressions, schema violations, sentiment, and other production signals. We've written more about the approach here: https://blog.oodle.ai/you-cant-sample-your-way-to-reliable-a...

The combination of our own engine, no sampling, and deterministic processing before LLM-for-evals allows us to price at $10 per million traces, provide sub-second p99 query latency, and have healthy margins. Before building this, we used Langfuse for our own agent observability, which was 6x more expensive.

Still super early, and rough around some edges, we would love your questions and feedback!

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camel_gopher 2 hours ago | parent | next [-]

Dang that’s expensive. We pay $0.75/M through a vendor

	▲	mvijaykarthik an hour ago \| parent \| next [-]
		We price per GB of ingested trace - $0.3/GB, goes lower as you scale. Traditional APM spans are ~2KB - this would come to ~$0.6/million spans. How we arrived at $10 is that we assumed each agent span is ~35KB. Which means 1M spans is ~35GB - which comes to ~$10. Agent spans are larger because they have large prompts. If your LLM spans are smaller, the cost would be lower. For our customers we see this vary between 20-30KB, and we took a conservative 35KB number.
	▲	kirankgollu 2 hours ago \| parent \| prev [-]
		Good to know. Could you share your vendor and capabilities and pricing page please?

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mvijaykarthik 4 hours ago | parent | prev | next [-]

Hi HN, Vijay here

Adding support for agent traces turned out to be a great learning experience - it pushed us to rethink and replace parts of our storage engine https://blog.oodle.ai/how-we-achieved-10-million-agent-spans...

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govarun 3 hours ago | parent | prev | next [-]

love oodle’s speed and the best in class mcp. excited to try out agent tracing and evaluate the accumulated failure patterns

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add-sub-mul-div 3 hours ago | parent | prev | next [-]

The self-promotion spam will continue until the community improves.

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georgemcbay 2 hours ago | parent | prev [-]

"Oodle" to me will always be the compression library first and foremost, just like "pi" will always make me think first of the Raspberry Pi rather than the coding agent.

Perhaps someone should vibecode a product that allows AI developers to generate project names that don't come with confusing collision baggage.